Papers Sound Classification
“Sound Classification” 태그가 달린 논문 148편 · 필터 해제
Tiny Transformers for Environmental Sound Classification at the Edge
With the growth of the Internet of Things and the rise of Big Data, data processing and machine learning applications are being moved to cheap and low size, weight, and power (SWaP) devices at the edge, often in the form…
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationLearning spectro-temporal representations of complex sounds with parameterized neural networks
Deep Learning models have become potential candidates for auditory neuroscience research, thanks to their recent successes on a variety of auditory tasks. Yet, these models often lack interpretability to fully understand…
Action DetectionActivity DetectionSound ClassificationSpeaker VerificationEnvironmental Sound Classification on the Edge: A Pipeline for Deep Acoustic Networks on Extremely Resource-Constrained Devices
Significant efforts are being invested to bring state-of-the-art classification and recognition to edge devices with extreme resource constraints (memory, speed, and lack of GPU support). Here, we demonstrate the first d…
Audio ClassificationEnvironmental Sound ClassificationGPUModel Compression+2SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification
Environmental Sound Classification (ESC) is a challenging field of research in non-speech audio processing. Most of current research in ESC focuses on designing deep models with special architectures tailored for specifi…
Contrastive LearningData AugmentationEnvironmental Sound ClassificationEnvironment Sound Classification+3Comparison of semi-supervised deep learning algorithms for audio classification
In this article, we adapted five recent SSL methods to the task of audio classification. The first two methods, namely Deep Co-Training (DCT) and Mean Teacher (MT), involve two collaborative neural networks. The three ot…
Audio ClassificationAudio TaggingData AugmentationDeep Learning+3Contrastive Self-Supervised Learning of Global-Local Audio-Visual Representations
Contrastive self-supervised learning has delivered impressive results in many audio-visual recognition tasks. However, existing approaches optimize for learning either global representations useful for high-level underst…
ClassificationDeepFake DetectionFace SwappingGeneral Classification+4Urban Sound Classification : striving towards a fair comparison
Urban sound classification has been achieving remarkable progress and is still an active research area in audio pattern recognition. In particular, it allows to monitor the noise pollution, which becomes a growing concer…
Audio ClassificationAudio TaggingClassificationEnvironmental Sound Classification+2Respiratory Sound Classification Using Long-Short Term Memory
Developing a reliable sound detection and recognition system offers many benefits and has many useful applications in different industries. This paper examines the difficulties that exist when attempting to perform sound…
blind source separationClassificationGeneral ClassificationSound ClassificationLungRN+NL: An Improved Adventitious Lung Sound Classification Using Non-Local Block ResNet Neural Network with Mixup Data Augmentation
Performing an automated adventitious lung sound detection is a challenging task since the sound is susceptible to noises (heart-beat, motion artifacts, and audio sound) and there is subtle discrimination among different …
Audio ClassificationData AugmentationLung Sound ClassificationSound ClassificationAn Ensemble of Convolutional Neural Networks for Audio Classification
In this paper, ensembles of classifiers that exploit several data augmentation techniques and four signal representations for training Convolutional Neural Networks (CNNs) for audio classification are presented and teste…
Audio ClassificationClassificationData AugmentationEnvironmental Sound Classification+2A Robust Interpretable Deep Learning Classifier for Heart Anomaly Detection Without Segmentation
Traditionally, abnormal heart sound classification is framed as a three-stage process. The first stage involves segmenting the phonocardiogram to detect fundamental heart sounds; after which features are extracted and cl…
Anomaly DetectionClassificationExplainable artificial intelligenceGeneral Classification+2Deep Neural Network for Respiratory Sound Classification in Wearable Devices Enabled by Patient Specific Model Tuning
The primary objective of this paper is to build classification models and strategies to identify breathing sound anomalies (wheeze, crackle) for automated diagnosis of respiratory and pulmonary diseases. In this work we …
Anomaly DetectionGeneral ClassificationQuantizationSound ClassificationESResNet: Environmental Sound Classification Based on Visual Domain Models
Environmental Sound Classification (ESC) is an active research area in the audio domain and has seen a lot of progress in the past years. However, many of the existing approaches achieve high accuracy by relying on domai…
ClassificationEnvironmental Sound ClassificationGeneral ClassificationSound ClassificationAcoustic Scene Analysis using Analog Spiking Neural Network
Sensor nodes in a wireless sensor network (WSN) for security surveillance applications should preferably be small, energy-efficient, and inexpensive with in-sensor computational abilities. An appropriate data processing …
ClassificationGeneral ClassificationSound ClassificationEnvironmental Sound Classification with Parallel Temporal-spectral Attention
Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC). Recently, temporal attention mechanisms have been used in CNN to capture the u…
Acoustic Scene ClassificationAudio ClassificationClassificationEnvironmental Sound Classification+3LungBRN: A Smart Digital Stethoscope for Detecting Respiratory Disease Using bi-ResNet Deep Learning Algorithm
Improving access to health care services for the medically under-served population is vital to ensure that critical illness can be addressed immediately. In the scenarios where there is a severely lacking of skilled medi…
Audio ClassificationDiagnosticLung Sound ClassificationSound ClassificationImproving Universal Sound Separation Using Sound Classification
Deep learning approaches have recently achieved impressive performance on both audio source separation and sound classification. Most audio source separation approaches focus only on separating sources belonging to a res…
Audio Source SeparationClassificationGeneral ClassificationSound ClassificationSpectrogram-frame linear network and continuous frame sequence for bird sound classification
Inspired by that bird sound has various frequency distributions and continuous time-varying properties, a novel method is proposed for the classification of bird sound based on continuous frame sequence and spectrogram-f…
Sound ClassificationDetection of Adversarial Attacks and Characterization of Adversarial Subspace
Adversarial attacks have always been a serious threat for any data-driven model. In this paper, we explore subspaces of adversarial examples in unitary vector domain, and we propose a novel detector for defending our mod…
BenchmarkingEnvironmental Sound ClassificationregressionSound ClassificationUrban Sound Tagging using Convolutional Neural Networks
In this paper, we propose a framework for environmental sound classification in a low-data context (less than 100 labeled examples per class). We show that using pre-trained image classification models along with the usa…
Data AugmentationEnvironmental Sound ClassificationGeneral Classificationimage-classification+2